The world is drowning in data. From social media
interactions to financial transaction, scientific experiments to online
shopping, there is a lot of information generated in every aspect of our lives.
Imagine you have a huge pile of puzzle pieces, but you have no idea what the
final picture is. Data Analytics is that field which analyzes a wide range of
data and segregates the relevant data, that would help the respective
organization in performing their tasks.
AI is like a super-smart puzzle solver. It can quickly
look at all the pieces, find patterns, and even guess what the missing pieces
might be. AI does this in a few ways: It’s like teaching a computer to learn
from examples. You show it lots of data, and it figures out the rules and
patterns on its own. This helps it make predictions and find things you might miss. Another way is
Natural Language Processing. It is like giving computers the ability to
understand human language. This help them analyze text data, like customer
reviews or social media posts, to understand what people are saying and feeling.
The main goal of AI in Data Analytics is to Support, Automate, and Simplify
each stage of the data analysis journey. AI in Data Analytics can help improve
speed and efficiency and can help in the automation of tasks. Imagine trying to
read through millions of documents-it would take forever! AI can do it in seconds,
finding trends and relationship that humans might miss. AI can handle both
structured and unstructured data, and can be used to analyze large amounts of
data at a high speed. It can be used to identify patterns and can be used to
provide predictive insights. AI chooses the best machine learning model for a
particular problem based on data characteristics and performance. The impact of
AI on data analysis extends beyond specific applications. It is changing the
way we approach data itself, such as data visualization tools that can present
difficult/complex data in an interactive, connected and bilateral ways, making
it easier for analysts to understand and communicate their findings.AI helps
prepare data for analysis, including data cleaning and organization, training
machine models, interpreting trends, preprocessing. AI is making data analysis
faster, easier, and more powerful. It’s helping us find hidden insights, make
better decisions and solve problems we couldn’t before. The role of AI in data
analysis is multifaceted, with a wide range of techniques and applications. The
benefits of AI in data analysis are that, it analyzes data much faster than
humans, it reduces errors and biases, it is available 24/7 and improves
productivity. AI also enables data governance and security which help
organizations to manage and protect their data more wisely and effectively.
Data analysis is everywhere! Think about how your
phone, laptop suggests apps you might like, or how Netflix recommends movies.
AI is constantly analyzing your usage patterns to make those suggestions and personalized
recommendations, when you shop online. AI analyzes your past purchases and
browsing history to suggest products you might like. This is also how streaming
services like Netflix and Spotify recommend content. Apps like Google Maps use
real-time traffic data to suggest the fastest routes.AI analyzes traffic
patterns, accidents, and road closures to help you avoid delays. All of these
are examples of data analysis in action. SIRI is an example of AI used in data
analysis. Siri, like other virtual assistants, uses Natural Language Processing
(NLP) and Machine Learning algorithms to analyze voice data and perform tasks. The
major functions of Siri is to assist with task and answer questions, analyze
voice data to understand the user info and provide relevant responses. Siri
identifies entities like name, locations and organizations to provide more
accurate responses. While the primary focus of Siri is on user interaction. Similarly,
other virtual assistants like Alexa, Google Assistant, and Bixby also use AI
data analysis to provide insights and perform tasks. Finance and Banking,
Healthcare, Retail and E-commerce, Marketing and advertising, Government and
public sector are industries that employ Data Analytics. Data analysts are hired
in many industries, to help organizations in taking appropriate and effective
decisions. By analyzing data, they provide valuable result that improve operation,
product and services.
Is AI replacing
data analysts?
AI is not replacing data analysts, but rather boost
and increase their work. AI tools can automate some tasks, but human analysts
are still needed for problem solving, critical thinking, judgements and
stylistic result. It can do the boring stuff like cleaning and organizing data.
So, AI helps data analysts work faster and smarter,
but it won’t take their jobs.
Data analyst are essential in today’s world, helping
organizations make better decisions
More effectively and efficiently and driving business success.
It’s a team effort! Data scientists, software engineers, and data analysts all
work together to create analytics solutions. Configuration and continuously
managing the analytics environment.
Connecting data sources with the analytics. Creating
separate environments, organizing users into user groups and manage permissions,
implementing security measures to ensure data integrity, Customizing the
environments analytics such as branding, custom themes and logos. In
conclusion, AI is transforming the role of data analysts, but not replacing
them human analysts capabilities, enable them to process large data set
quickly, Identify patterns(lead to new discoveries and innovation),automate
routine work and focus on high-level tasks strategies. The collaboration
between AI and human analysts unlocks the full potential of data analysis, driving
better decision-making and outcomes.
Written by MANYA
PROJECT CUM INTERNSHIP STUDENT
VERIDICAL TECHNOLOGIES
9319593915
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